Algorithms Are Streamlining the House Hunting Process

At its most basic, an algorithm is a code-breaking tool. It takes the totality of data provided to it, finds patterns and links, and executes its given task according to a strict set of instructions.

And at its most complex, an algorithm is a wildly beneficial tool for sifting through big data and closely mirroring the human thought process to solve a problem.

It’s an understatement to say that AI algorithms have transformed the real estate industry. Before them, the industry and its practitioners worked on an inefficient combo of gut instinct and surface-level research. Now, real estate consumers can leverage fast, accurate, comprehensive algorithmic tools to get the home they want, the agent they need and the mortgage they deserve.

Here are three critical ways algorithms are streamlining the house-hunting process.

Flexible Match Scores for Home Searches

The most popular type of algorithm in current real estate technology is the “home search match score.” You see it leveraged by numerous listing marketplaces, each mobilizing its own (slightly different) algorithm. It’s the core technology underpinning sites like Zillow and Redfin, but it’s also a feature of end-to-end platforms like Nobul (more on them in a moment).

Basically, a home search matching algorithm takes all of that consumer criteria you might normally tell an agent – where you want to live, what neighbourhoods you like, whether you value tranquillity or nightlife, etc. – and the algorithm recommends properties.

Crucially, however, the algorithm remains flexible. It doesn’t just give you the properties that satisfy every criterion; it also offers options in the margins. “We try to replicate the human experience of discussing what trade-offs people are willing to make online,” says Homes.com’s David Mele, which he says “eliminates the tyranny of rigid filters.”

Realtor Matchmaking Algorithms

One of the most exciting applications of AI-powered algorithms is happening over at Nobul. The burgeoning real estate digital marketplace uses a proprietary algorithm to match consumers with their perfect agents.

The process is relatively straightforward (even if the supporting technology isn’t). Buyers/sellers enter their criteria for an agent (e.g., verified ratings, sales history, commission cost). The algorithm accesses stores of data only available to Nobul (the company is big on industry transparency!) And then, the algorithm heads to work finding the ideal local agents for that buyer/seller, providing the consumer with match scores for each option.  

“We’re solving a different problem compared to others in the industry,” CEO and founder Regan McGee told Medium. “We are working towards getting consumers the best possible experience at the best possible value for their real estate transaction.”

Finding the Perfect Mortgage

Mortgage searching algorithms round out the so-called holy trinity of modern real estate algorithms. You’ve got your agent; you’ve found your dream home; now, you need the right mortgage behind you.

According to CNBC, “Algorithms can now go through millions of documents in seconds, looking through property values, debt levels, home renovations, and even some of a homeowner’s personal information,” all in a bid to “help find buyers the perfect mortgage.” Like the previous items on this list, the process starts with consumers inputting their information and answering some basic questions. The algorithm then combs through tens of thousands of mortgage options to pinpoint ideal solutions. Experts hope that this newly tech-enabled process will help mitigate risk for lenders and borrowers.

The real estate industry has always been flush with data. But until recently, the industry didn’t really know what to do with it. Now, with the advent of AI algorithms, innovative companies like the ones above use algorithms like a key – to help prospective homebuyers unlock their dream home.

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